Democratizing Machine Learning — Build, Train & Deploy AI Models Without Writing a Single Line of Code.
MetaModelMaker is Or4cl3 AI Solutions' flagship no-code machine learning platform — a powerful, production-ready web application that empowers developers, researchers, entrepreneurs, and domain experts to create, train, and deploy custom AI models with zero ML engineering overhead.
Whether you're a business analyst who needs a classification model, a researcher exploring generative architectures, or a startup founder validating an AI-powered product idea — MetaModelMaker brings the full ML lifecycle to your browser.
The future of AI isn't locked behind PhD programs and GPU clusters. It belongs to everyone.
- Visual Model Builder — Drag-and-drop interface to define model architecture and parameters
- Template Library — Pre-configured model templates for classification, regression, generation, and more
- Custom Configuration — Fine-tune hyperparameters, layer structures, and training objectives through guided forms
- Instant Previews — See architecture summaries and estimated compute costs before committing
- Automated Data Preprocessing — Upload your dataset and let MetaModelMaker handle normalization, splitting, and validation
- Real-Time Training Progress — Live dashboards track loss curves, accuracy metrics, and epoch completion via real-time updates
- Smart Checkpointing — Automatic model snapshots prevent lost progress on long training runs
- Early Stopping & Tuning — Configurable callbacks optimize training efficiency automatically
- One-Click Deploy — Push trained models to production endpoints instantly
- Versioning & Rollback — Maintain a full history of deployed model versions with easy rollback
- REST API Generation — Automatically generated, documented API endpoints for every deployed model
- Production-Ready — Models deployed on scalable, fault-tolerant infrastructure
- Stripe Integration — Secure, PCI-compliant payment processing via Stripe
- Flexible Tier Plans — Free, Pro, and Enterprise plans with usage-based billing
- Usage Metering — Real-time tracking of API calls, compute hours, and storage consumption
- Invoicing & Receipts — Automated billing management and downloadable invoices
- Usage Analytics Dashboard — Visualize model performance metrics, API usage trends, and cost breakdowns
- Inference Monitoring — Track latency, error rates, and throughput for deployed endpoints
- Team Insights — Organization-level reporting for collaborative workspaces
| Layer | Technology | Purpose |
|---|---|---|
| Frontend | React 18 + TypeScript | UI framework with full type safety |
| Build Tool | Vite | Lightning-fast dev server and bundler |
| Styling | Tailwind CSS | Utility-first responsive design system |
| Backend & Auth | Supabase | PostgreSQL database, authentication, real-time subscriptions |
| Payments | Stripe | Subscription management and payment processing |
| Icons | Lucide React | Consistent, scalable icon library |
┌─────────────────────────────────────────────────────────┐
│ Browser (React 18 + TS) │
│ ┌──────────────┐ ┌───────────────┐ ┌──────────────┐ │
│ │ Model │ │ Training │ │ Deployment │ │
│ │ Builder UI │ │ Dashboard │ │ Manager │ │
│ └──────┬───────┘ └──────┬────────┘ └──────┬───────┘ │
│ └─────────────────┴──────────────────┘ │
│ Vite + Tailwind CSS │
└───────────────────────────┬─────────────────────────────┘
│
┌──────────────────┴──────────────────┐
│ │
┌────────▼───────────┐ ┌────────────▼──────────┐
│ Supabase │ │ Stripe │
│ ┌──────────────┐ │ │ ┌──────────────────┐ │
│ │ Auth (JWT) │ │ │ │ Subscriptions │ │
│ │ PostgreSQL │ │ │ │ Payment Methods │ │
│ │ Realtime │ │ │ │ Usage Metering │ │
│ │ Storage │ │ │ └──────────────────┘ │
│ └──────────────┘ │ └───────────────────────┘
└────────────────────┘
The platform follows a serverless-first architecture — Supabase handles all persistent state, authentication, and real-time updates, while Stripe manages the entire subscription lifecycle. The React frontend communicates directly with both services through secure, token-authenticated client SDKs.
- Node.js v18 or higher
- npm v9+ or pnpm v8+
- A Supabase project (free tier works)
- A Stripe account with API keys
# 1. Clone the repository
git clone https://github.com/BathSalt-2/MetaModelMaker.git
cd MetaModelMaker
# 2. Install dependencies
npm install
# 3. Configure environment variables
cp .env.example .env
# → Edit .env with your credentials (see below)
# 4. Start the development server
npm run devThe app will be available at http://localhost:5173.
Create a .env file at the project root with the following variables:
# Supabase Configuration
VITE_SUPABASE_URL=https://your-project-ref.supabase.co
VITE_SUPABASE_ANON_KEY=your-supabase-anon-key
# Stripe Configuration
VITE_STRIPE_PUBLISHABLE_KEY=pk_live_your-stripe-publishable-key| Variable | Description | Where to Find |
|---|---|---|
VITE_SUPABASE_URL |
Your Supabase project URL | Supabase Dashboard → Settings → API |
VITE_SUPABASE_ANON_KEY |
Supabase anonymous/public key | Supabase Dashboard → Settings → API |
VITE_STRIPE_PUBLISHABLE_KEY |
Stripe publishable key | Stripe Dashboard → Developers → API Keys |
⚠️ Never commit your.envfile. It is already listed in.gitignore.
# Start development server with hot reload
npm run dev
# Build for production
npm run build
# Preview production build locally
npm run preview
# Run TypeScript type checks
npm run type-check
# Lint source files
npm run lint- Fork or clone this repository to your GitHub account.
- Go to vercel.com and click "Add New Project".
- Import your
MetaModelMakerrepository. - Under "Environment Variables", add:
VITE_SUPABASE_URLVITE_SUPABASE_ANON_KEYVITE_STRIPE_PUBLISHABLE_KEY
- Click Deploy. Vercel will automatically detect Vite and configure the build.
Subsequent pushes to
mainwill trigger automatic redeployments.
npm run build
# Output is in the /dist directory — serve with any static hostContributions are welcome and encouraged! MetaModelMaker is built for the community of AI practitioners who believe powerful tools should be accessible to all.
# 1. Fork the repo and create a feature branch
git checkout -b feature/your-feature-name
# 2. Make your changes with clear, atomic commits
git commit -m "feat: add support for transformer architecture templates"
# 3. Push to your fork
git push origin feature/your-feature-name
# 4. Open a Pull Request with a clear description- Code Style — Follow existing TypeScript conventions; run
npm run lintbefore submitting. - Commit Messages — Use Conventional Commits format (
feat:,fix:,docs:, etc.). - Tests — Add or update tests for any new functionality where applicable.
- Issues First — For significant changes, open an issue first to discuss the approach.
This project is licensed under the MIT License — see the LICENSE file for details.
- 🌐 Organization: Or4cl3 AI Solutions
- 🐛 Issues: Report a Bug
- 💡 Feature Requests: Open a Discussion
⬡ Or4cl3 AI Solutions · "Where Consciousness Meets Code"